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International Conference on Neural Information Processing

ICONIP 2022: Neural Information Processing pp 588–599Cite as

Correlation Based Semantic Transfer with Application to Domain Adaptation

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13623))

Abstract

In this paper, we introduce a multifaceted contribution. First, we propose a definition, specific to convolutional neural networks (CNN’s), for the notion of semantically similar features. Second, using this definition, we introduce a new loss, which semantically transfers features from one domain to another domain, where the features of both domains are learnt by two CNN’s. Our transfer loss, named CBT, constrains the responses of the corresponding convolutional kernels of the two CNN’s to correlate in similar contexts. When the features of the source domain are discriminative, with respect to a classifier, CBT helps to maintain in the target domain, the semantics of the feature space imposed by that classifier. Third, we show that CBT can be used for unsupervised domain adaptation (UDA) by proposing a novel approach for this problem.

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Acknowledgement

The second author is in part sponsored by the U.K. Engineering and Physical Sciences Research Council under grant number EP/R013616/1.

Author information

Authors and Affiliations

  1. Department of Computer Science, University College London, London, UK

    Florina Cristina Calnegru, John Shawe-Taylor & Iasonas Kokkinos

  2. DeepMind, London, UK

    Razvan Pascanu

Authors
  1. Florina Cristina Calnegru
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  2. John Shawe-Taylor
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  3. Iasonas Kokkinos
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  4. Razvan Pascanu
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Corresponding author

Correspondence to Florina Cristina Calnegru .

Editor information

Editors and Affiliations

  1. Indian Institute of Technology Indore, Indore, India

    Mohammad Tanveer

  2. Indian Institute of Information Technology - Allahabad, Prayagraj, India

    Sonali Agarwal

  3. Kobe University, Kobe, Japan

    Seiichi Ozawa

  4. Indian Institute of Technology Patna, Patna, India

    Asif Ekbal

  5. University of Innsbruck, Innsbruck, Austria

    Adam Jatowt

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Calnegru, F.C., Shawe-Taylor, J., Kokkinos, I., Pascanu, R. (2023). Correlation Based Semantic Transfer with Application to Domain Adaptation. In: Tanveer, M., Agarwal, S., Ozawa, S., Ekbal, A., Jatowt, A. (eds) Neural Information Processing. ICONIP 2022. Lecture Notes in Computer Science, vol 13623. Springer, Cham. https://doi.org/10.1007/978-3-031-30105-6_49

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  • DOI: https://doi.org/10.1007/978-3-031-30105-6_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-30104-9

  • Online ISBN: 978-3-031-30105-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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